Special Report, Americas, Health
The problem with this theory is that the initial shift from wolf-like to dog-like traits could only have happened very slowly. Wolves are relatively uniform in appearance, so the odds of a mutation appearing randomly in a captive population are small. It would have taken many thousands or even millions of years to get much diversity. Yet fossil evidence shows that dogs appeared not all that long ago. If it's true that dogs have existed for only about 15,000 years, this is a blink of the eye in evolutionary terms. DNA evidence indicates that dogs may have begun to split with wolves as many as 100,000 years ago, but this is still relatively recent. Yet in dogs we see some of the most extreme physical diversity of any mammalian species. There is more variation in size, color, coat texture and other aspects of appearance within dogs than there is among all other members of the canid family. Recent publications, such as the controversial book "Dogs: A Startling New Understanding of Canine Origin, Behavior, & Evolution," by Raymond and Lorna Coppinger, present an alternative theory for the way that dogs evolved from wolves.|Efficient and adaptive computer vision systems have been proposed to make computer vision tasks, such as image classification and object detection, optimized for embedded or mobile devices. These solutions, quite recent in their origin, focus on optimizing the model (a deep neural network, DNN) or the system by designing an adaptive system with approximation knobs. In spite of several recent efforts, we show that existing solutions suffer from two major drawbacks. First, the system does not consider energy consumption of the models while making a decision on which model to run. Second, the evaluation does not consider the practical scenario of contention on the device, due to other co-resident workloads. In this work, we propose an efficient and adaptive video object detection system - Virtuoso, which is jointly optimized for accuracy, energy efficiency, and latency. Underlying Virtuoso is a multi-branch execution kernel that is capable of running at different operating points in the accuracy-energy-latency axes, and a lightweight runtime scheduler to select the best fit execution branch to satisfy the user requirement.
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